################################
#	John Henderson
#	Gerrymandering Incumbency 
#		(with Brian Hamel and Aaron Goldzimer)
#		April 9, 2017    
#
################################
# code edits that produced by Chen & Rodden (2013), to replicate their 2000 analysis 
#  for competitiveness outcomes                                                 
################################
# calls sims2000.R to load data for plotting

rm(list=ls())    

GetColorHexAndDecimal <- function(color)
{
  c <- col2rgb(color)
  sprintf("#%02X%02X%02X %3d %3d %3d", c[1],c[2],c[3], c[1], c[2], c[3])
}

library(stringr)  
library(foreign)

setwd("~/Dropbox/StateRedistricting/replication/short/")
source('sims2010.R')

#########################
# cd vertical
#########################

{
pdf(width=5,height=9,file='figure1a.pdf')
plot(x=-1000, y=-1000, type='n', xlim=c(-.09, .5), ylim=c(.5,43), axes=F, ylab="", xlab="")#, main=paste("Margins of Victory in House Elections\n",state,sep=""))
axis(1,at=c(0,.1,.2,.3,.4,.5),labels=c(0,.1,.2,.3,.4,.5))
#cnts=0
cnts=44    


#legend(cex=.7,y=cnts-12.25,x=.328,border=F,box.lty=1,legend=c('Enacted Plan','Simulated Plan'),	
# col=c('red',gray(.65)),lwd=c(1,1),pch=c(1,19),lty=c(NA,NA))
pcc=17

#Means and Medians
for (state in states_ix){
	cnts=cnts-1
	
	#Means :: average over simulatons, i.e., counterfactual districtings
	means.sim=as.numeric(sims[which(sims[,1]==state),2:ncol(sims)])
	mean.10=election08[which(names(election08)==state)]
	
	#hypothesis-test-like statistics
	if(length(mean.10)>0){
		mu=mean(means.sim,na.rm=T)
		sds=sd(means.sim,na.rm=T) 
		s.means.sim=((means.sim-mu)/sds)
		s.mean.10=((mean.10-mu)/sds)	
		s.dif=mean(s.mean.10-s.means.sim)
		if(s.dif>0){
			p.dif=sum(s.mean.10<s.means.sim)/length(s.means.sim)    
		} else{                                                     
			p.dif=sum(s.mean.10>s.means.sim)/length(s.means.sim)    
		}
	} else{
		p.dif=1
		s.dif=NA
	}     
	
	cols='red' 
	ltys=2
	if(p.dif<.05){
		cols='red' 
		ltys=1
	}
	
	if(length(mean.10)>0){ 	 
		points(x=means.sim, y=jitter(factor=.2,rep(cnts,length(means.sim))), col=gray(.65), lwd=2,pch=pcc,cex=.52)
		points(y=cnts, x=mean.10, col=cols, pch=1,cex=sqrt(1+abs(s.dif))/1.25,lty=2) 	
	  			
		text(col='black',adj=c(0,NA),x=.004,y=cnts,labels=paste('(',str_sub(s.dif,1,str_locate(s.dif,pattern='[/.]')[1]+2),')',sep=''),srt = 1, pos = 2,cex=.5)				
	} else{
		text(col='black',adj=c(0,NA),x=.004,y=cnts,labels='NA',srt = 1, pos = 2,cex=.5)				
	}                                                                                           
	
	text(adj=c(0,NA),x=-.055,y=cnts,labels=as.character(state),srt = 1, pos = 2,cex=.65)
}         
                            
# lines and legend graphics   
lines(col='grey',lty=2,y=c(.5,.5),x=c(-.0515,.5))
lines(col='grey',lty=2,y=c(4.5,4.5),x=c(-.0515,.5))  
lines(col='grey',lty=2,y=c(13.5,13.5),x=c(-.0515,.5))
lines(col='grey',lty=2,y=c(21.5,21.5),x=c(-.0515,.5))
lines(col='grey',lty=2,y=c(37.5,37.5),x=c(-.0515,.5))
lines(col='grey',lty=2,y=c(43.5,43.5),x=c(-.0515,.5))                              
                                          
axis(2,line=-1.5,at=c(.5,4.5,13.5,21.5,37.5,43.5),labels=F,tck=-.02)

text(x=.5-.0105,y=42.,labels='Democratic',cex=.75,adj=c(1,1),srt=0)
text(x=.5-.0105,y=36.,labels='Republican',cex=.75,adj=c(1,1),srt=0)
text(x=.5-.0105,y=20.,labels='Bipartisan',cex=.75,adj=c(1,1),srt=0)
text(x=.5-.0105,y=12.,labels='Court',cex=.75,adj=c(1,1),srt=0) 
text(x=.5-.0105,y=3.,labels='Independent',cex=.75,adj=c(1,1),srt=0) 
mtext("Mean Expected Margin of Victory",side=1,at=.25,adj=.5,line=3)
dev.off()
}

#end  